System and method to manage a quality of delivery of healthcare

ABSTRACT

A system and method to manage a quality of delivery of healthcare to a patient. The method includes tracking completion of a portion of a protocol associated with one of a series of candidate hypotheses to deliver healthcare to the patient; tracking a change in a quality of care metric directed to the patient with completion of a portion the protocol, the quality of metric including at least one of a time to rate of reduction in a health risk to the patient and a time to or rate of reduction in symptom or abnormal biometric data of the patient; and outputting an alert in response to the quality of care metric exceeding a threshold.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit as a continuation of andpriority to U.S. patent application Ser. No. 12/241,193, filed on Sep.30, 2008, for “System and Method to Manage a Quality of Delivery ofHealthcare,” which is incorporated herein by reference in its entirety.

BACKGROUND

The subject herein generally relates to a system and method to manage aquality of delivery of healthcare to a patient, and more specifically,to automatically track reduction of health risk to the patient withprogression through a protocol to treat the patient.

Hospitals and other medical facilities (e.g., imaging centers,cardiology treatment centers, emergency rooms, surgical suites, etc.)include various workflows to deliver diagnosis or treatment to admittedpatients. These workflows are comprised of events that employ variousresources, such as imaging rooms, physicians, nurses, radiologists,cardiologists, clinicians, technicians, etc.

Typically, delivery of medical care includes criticality to a time ofdelivery (such as to prevent irreversible damage or likelihood ofmortality). For example, in the case of cardiac care, delivery ofcritical care with respect to a cardiac failure can have an estimatedtime criticality of less than 4 hours to prevent irreversible damage andpatient mortality. As such, cardiac car remains a significant healthcare issue, where first diagnosis can happens in the emergency medicaldepartment. There are also numerous other critical medical conditionsthat similarly require urgent medical intervention within asignificantly short period of time.

A certain known method of standard of care can be referred to as“evidence based medicine” that includes integrating individual clinicalexpertise with evidence based external best practices. However, at leastone problem of the evidence based medicine technique can include how tointegrate clinical expertise with evidence based external best practicesin view of a growth rate of clinical knowledge that exceeds humanability to assimilate.

The above-mentioned problem can be addressed by the subject matterdescribed herein in the following description.

BRIEF SUMMARY

The system and method of the subject matter described herein can bedirected to manage a quality of delivery of medical care providedthrough a number of external and internal factors. The system and methodcan provide for the repeatable, reliable delivery of healthcare, as wellas generally rapid, repeatable, reliable decision support to clinicalstaff that can reduce variance in a delivery of healthcare and therebyimprove quality of healthcare delivery and provide a more structuredprocess to diagnostic investigation.

According to one embodiment, a method to manage a quality of delivery ofhealthcare to a patient. The method comprises the steps of trackingcompletion of a portion of a protocol associated with one of a series ofcandidate hypotheses to deliver healthcare to the patient; tracking achange in a quality of care metric directed to the patient withcompletion of a portion the protocol, the quality of metric including atleast one of a time to rate of reduction in a health risk to the patientand a time to or rate of reduction in symptom or abnormal biometric dataof the patient; outputting an alert in response to the quality of caremetric exceeding a threshold.

According to another embodiment, a system to manage delivery ofhealthcare to a patient. The system comprises a database having a seriesof templates, each template comprising at least one keyword associatedwith a medical condition and a protocol to diagnose or treat, and acontroller with a memory in communication with a processor. The memoryincludes program instructions for execution by the processor to performthe steps of: tracking completion of a portion of a protocol of thetemplate associated with one of a series of candidate hypotheses todeliver healthcare to the patient, tracking a change in a quality ofcare metric directed to the patient with completion of a portion theprotocol, the quality of metric including at least one of a time to rateof reduction in a health risk to the patient and a time to or rate ofreduction in symptom or abnormal biometric data of the patient, andoutputting an alert in response to the quality of care metric exceedinga threshold.

Various other features, objects, and advantages of the invention will bemade apparent to those skilled in the art from the accompanying drawingsand detailed description thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic overview of an embodiment of system to manage aworkflow.

FIG. 2 is a flow diagram illustrating an embodiment of a method tomanage the workflow with the system of FIG. 1.

FIG. 3 is a schematic diagram illustrating an embodiment of operation ofthe system of FIG. 1 to manage delivery of healthcare to a patient.

FIG. 4 is a schematic diagram of a dashboard comprising output of thesystem of FIG. 1.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings that form a part hereof, and in which is shown byway of illustration specific embodiments that may be practiced. Theseembodiments are described in sufficient detail to enable those skilledin the art to practice the embodiments, and it is to be understood thatother embodiments may be utilized and that logical, mechanical,electrical and other changes may be made without departing from thescope of the embodiments. The following detailed description is,therefore, not to be taken as limiting the scope of the invention.

FIG. 1 illustrates a schematic diagram of an embodiment of a system 100to manage resources 105 (e.g., physician or surgeon or other staff 108,medical equipment 110, laboratory systems 112, etc.) in the delivery ofhealthcare to patients 115. An embodiment of the system 100 includesagents 120 in communication (via wired or wireless connection) with acentral server or controller 125.

An embodiment of the agent 120 generally includes computer-readableprogram instructions in or not in combination with one or more devices(e.g., clocks, timers, blood pressure monitors, electrocardiogram (ECG)monitors, temperature monitors, etc.) operable to track properties 130(e.g., quality metrics such as wait time or biometric data such as bloodpressure, pulse, respiration rate, laboratory results, etc.) associatedwith each patient 115. Each agent 120 can be generally operable toacquire data of the measured changes in the properties 130 associatedwith each of the patients 115. The agent 120 can be created uponintroduction or admission of the patient 115 into the workflow. Theagent 120 can be generally operable to communicate or collaborate ingeneral real-time with one another, as well as with the patient 115.FIG. 1 shows the agent 120 located at the respective patient 115,respectively. Yet, it should be understood that one or more of theagents 120 or portions thereof can otherwise be located at the centralserver or controller 125.

One embodiment of the agent 120 can be configured to sense, detect, ortrack a presence and an awareness. Presence generally refers to anability of the agent 120 to express or communicate a current state ofactivity (e.g., available, partially in-use, fully in use, etc.) ofitself to other agent 120 in the system 100. Awareness generally refersto an ability of the agent 120 to sense the presence (as describedabove) of other agent 120 in the system 100. For example, awareness caninclude an ability of one agent 120 to track the activities of the agent120 or patients 115 correlated thereto in the workflow. The combinationof presence and awareness enables each agent 120 to initiate acommunication or collaboration with one another to identify or calculatea length of time to get a response from one another. Awareness alsoallows the agent 120 initiating a communication or collaboration withother agents 120 to make decisions about mode of communication (e.g.,route, wireless versus wired connection, etc.) to establish contactamongst multiple agents 120. An ability to express or communicate thepresence and leverage the awareness allows the agent 120 to initiatecommunications or collaboration with one another and to respond tocommunications from other agents 120 associated with other patients 115.

An example of the agent 120 can receive/communicate patient data,receive/communicate requests for a work order and a report status,receive/communicate patient notifications to report for an event or stepin the workflow (e.g., testing, imaging), receive/communicate problems,and receive/communicate orders for or results of tests. Examples ofagent 120 can also operable to contact respective physicians waiting forcritical patient information using an identified best mode ofcommunication (e.g., beeper, home telephone, email, cellular phone, textmessage, etc.). Additionally, physicians 110 or patients 115 cancommunicate via computer messaging system s or other known type of input(e.g., keyboard, touch-screen, voice recognition, etc.) with the agent120 in the workflow community to gain access to information andcollaborate with agent 120 at any given point in time of the workflow.

The series of agents 120 can include, or the system 100 can furtherinclude, an additional agent having a general ability to supervise ortrack all of the resources 105 and patients 115 in the workflow, andidentify or detect for errors (e.g., critical patient needs or wait timenot being met in a timely manner). Agent 120 may also representphysicians, which may be especially useful when team medicine isrequired to administer care in complex treatment situations.

The agent 120 can be programmed with instructions of the protocol todirect the patient through the resources (e.g., medical equipment orspace or personnel of the hospital diagnostic departments). The agent120 can acquire or track data of various properties (e.g.,consciousness, pulse, blood pressure, breathing rate, etc.) regardingthe patient's medical condition and/or interact with the personnel tooutput the appropriate level of urgency of the patient 115 for viewingby the staff 108. The agent 120 can also be operable to re-factor orschedule a sequence of tests or resources, if availability of oneprocedure or respective resource occurs earlier than a predicted orforecast sequence or schedule of the procedure or availability ofresources (unless there are medical reasons with respect to bio-markersetc, that drive such a need). The agent 120 can act as the patient'sproxy when negotiating tests.

The agent 120 can update databases of template 210 on completion of anytest, or any other instrumented data is taken. The agent 120 can alsoacquire or receive data from the various resources 105 (e.g., imagingsystem, PACS, physician, caregiver, staff, etc.) as institution managesthe medical condition of the patient 115. The agent 120 can leverage anincreased ability to gather information by the integration of patientcare management with the system 100. The system 100 can be generallyoperable via the agent 120 to track the dynamics of individual orpopulation of patients 115 over time and their respective needs anddemands on resources 105.

An embodiment of the controller 125 is connected in communication witheach of the agent 120. An embodiment of the controller 120 includes amemory or database 140 generally operable to receive updated values ormeasurements of tracked properties 130 on a continuous or periodic basisof the patient 115.

The controller 125 can also include a processor 145 generally configuredto execute program instructions stored in the memory 140. Although thememory 140 and processor 145 are shown at the controller 125, it shouldbe understood that the memory 140 or processor 145 can comprise remoteportions at the agent 120 or other components of the system 100.

The controller 125 can also be in communication with an input device 148and an output device 150. Examples of the input device 148 include akeyboard, an touch screen or graphic interface, mouse, toggle switches,etc. Examples of the output device 150 can include monitors,touch-screens or graphic interfaces, kiosks, dashboards, etc.

An embodiment of the system 100 can further a location sensing orlocation system 155 comprising sensing devices operable to track alocation of each patient 115 or resources. An embodiment of the locationsystem 155 is operable to communicate a location of each patient 115relative to a predetermined reference. The location system 155 can beoperable to track in coordinates, or by room or floor number, etc. Thelocation system 155 can be in wireless communication with the controller125. An embodiment of the location system 155 can employ electromagnetictechnology, radio frequency (rF) technology, optical technology, globalpositioning system (GPS) technology or combination thereof or otherposition measuring or locating technology known in the art.

FIGS. 2 and 3 include schematic diagrams to illustrate an embodiment ofa method 200 of operation of the system 100 to manage (e.g., scheduling)a quality of delivery of healthcare to the patient(s) 115 through eventsof the workflow. It should also be understood that the sequence of theacts or steps of the method 200 as discussed in the foregoingdescription can vary. Also, it should be understood that the method 200may not require each act or step in the foregoing description, or mayinclude additional acts or steps not disclosed herein. It should also beunderstood that one or more of the steps of the method 200 can berepresented as computer-readable program instructions for execution byone or more processors of the agent 120 or the controller 125.

Assume for sake of example that several conditions are possible forentry or admission of patient, including: a status of patient may beconscious, a patient may have medical history accessible through anElectronic Medical Record (EMR) 202, or a patient may be neitherconscious or an EMR 202 of the patient may be inaccessible or may notexist. The system 100 and method 200 of the subject matter canaccommodate each of the above-described scenarios. Also assume thatadmission can include a sequential assignment of a hospital admissionnumber that uniquely identifies each patient 115.

Step 205 includes creating a repository or database of templates 210each correlated to diagnosis of specific disease states or medicalconditions. An embodiment of step 205 includes creating and storing thetemplate 210 that comprises at least one symptom correlated to thedisease state or medical condition. Step 205 can include creatinginstructions to initiate at least one medical diagnostic protocol (e.g.,images to acquire, laboratory test to complete, etc.) 212, and storingor combining the instructions with the respective template 210.

The step 205 can further include communicating between the template 210and a database 208 (e.g., national, or international or medical advisoryrepository of healthcare standards and protocol 212 and performancemetrics). Examples of databases 208 can include an insurance providerdatabase to provide a more uniform national performance model to comparehealthcare provider institutions, protocols 212 authored locally at theinstitution, or provided by national organizations such as the AHA, ACCor other equivalent professional accredited institutions.

An embodiment of step 205 can further include storing a schedule of drugprescriptions or interaction within each template 210, or as astand-alone template 210. For example, there may be cases where negativedrug interaction states can compromise patient care, unintentionally orintentionally. The template 210 can include instructions to identify ordetect negative drug interactions or output a change (e.g., increase) tohealth risk (described in more detail below) correlated to one or moredrug interactions that can be stored or combined with the system. Theinstructions of the template 210 associated with negative druginteractions can also be represented as an automated protocol (e.g.,communicate instructions to schedule or request a set of tests orprocedures or acquisition of biometric data, instructions to execute analert/alarm) 212 associated with increased health risk to the patient115 caused by respective negative drug interaction.

Step 215 includes admitting the patient 115 to receive the delivery ofhealthcare. Step 215 can include obtaining or collecting at least onesymptom data of each patient 115 that can be stored or combined with thetemplate 210. An embodiment of the collecting step 215 can be performedthroughout the admission's process, including collecting symptom dataduring transport of the patient 115 in an ambulance to the hospital, orfrom an emergency call, or from relatives/onlookers. The symptom data(e.g., consciousness, complaints, symptoms, etc.) can be entered inresponse to questions illustrated on an interface, or free flowdiscussion with a healthcare provider.

Step 220 includes acquiring or creating the EMR 202 directed to thepatient 115. The acquired symptom data can be combined with newlycreated EMR 202 or with the historical data stored in a historical EMR202 directed to the patient 115. Step 225 includes creating the agent120 unique to the patient 115, the agent 120 as described in theabove-description of the construction of the system 100.

Step 230 includes interpreting or parsing at least the symptom data inaddition to all or portion of other historical or biometric data of theEMR 202, and transmitting or communicating an extraction of this data toa module of program instructions herein referred to as the decisionengine 235. An embodiment of step 230 includes the agent 120interpreting the symptom data and other acquired data as entered intothe EMR 202 of the patient 115, extracting the data from the EMR 202relative to symptom or other acquired data in the EMR 202, andintegrating the extracted data with a unique identifier forcommunication to the decision engine 235.

Step 240 includes interpreting or parsing the repository of templates210 in view of or for comparing to the acquired symptom data. Anembodiment of the decision engine 235 can parse the collected symptomdata for key words or symptom measurements or test result ranges via amodule of program instructions herein referred to as the symptomanalyzer 245. An embodiment of the symptom analyzer 245 can also beintegrated at the controller 125 or at the agent 120.

Step 250 includes generating or acquiring a series or list of hypotheses252 of the potential medical condition of the patient 115 forillustration to the healthcare provider (e.g., physician 108, etc.). Anembodiment of the hypotheses 252 can include a portion or more of thedata stored in the disease templates 210. Another embodiment of thesystem 100 may facilitate a decision or identification in accordance toa ranking of confidence 253 in multiple hypotheses 252. Based onavailable data, multiple hypotheses 252 can be ranked from most likelyto least likely, greatest to least confidence or confidence level 253,or vice versa, or combinations thereof.

Step 250 can further include calculating the risk factor, probability,or confidence 253 (e.g., probability or likelihood that one in the listof hypotheses 252 is correct diagnosis and/or treatment in delivery ofhealthcare to the patient) of each hypothesis 252 relative to another.One embodiment of the confidence level 253 can include a percentagematch of parsed terms from the patient EMR 202 that match keywordsassociated with the template 210, or predetermined confidence levels 253associated with prior medical history of patient associated with aparticular medical condition associated with template 210, or confidencelevel 253 associated with genetic risk factor of the patient to medicalcondition associated with template 210.

For example, a single symptom data representative or indicative of chestpain can suggest the series of hypotheses 252 to include a case ofindigestion. A combination of symptom data that includes symptom datarepresentative or indicative of chest pain accompanied with symptom datarepresentative or indicative of constricted breathing can suggest theseries of hypotheses 252 to include a case of an allergic response, orthe series of hypothesis 252 to include a case of an evolving cardiaccondition. The healthcare provider or physician 108 can scroll or scanthrough the list of hypotheses 252 output by the system 100 or method200. The system 100 or method 200 can also include output of indicatorsor instructions of possible diagnostic sequences or protocols 212associated with each hypotheses 252 for approval or designation by thephysician or caregiver 108. The system 100 or method 200 can alsoinclude outputting the risk factor or confidence 253 for each hypotheses252 for viewing and consideration by the physician. One or more of theabove-described steps can be repeated from admission through todischarge of the patient 115.

Step 260 includes receiving an instruction of a selection of a candidate262 from the series of hypotheses 252 for implementation. One embodimentof the system 100 may make a decision or selection of a candidate 262from the list of hypotheses 252 according to the confidence 253 in thecandidate 262 relative to the other hypotheses 252. Step 265 can includeautomatically outputting a protocol 212 of steps or schedule of tasks(e.g., acquire diagnostic image, electrocardiogram (ECG), stress test,etc.) to complete in response to the instruction of the selection ofcandidate hypothesis 262. Step 265 can include automatically initiatingand outputting a schedule of the resources 105 (e.g., imaging system,physician, staff, etc.) to complete the protocol 212 automatically inresponse to the instruction of the selection of the candidate hypothesis262. Assume that the template 210 associated with the candidatehypothesis 262 includes the instructions or steps and respectiveresources 105 to complete the protocol 212 on the patient 115.

Step 270 includes communicating the steps of the protocol 212 to orreceiving the steps of the protocol 212 at the agent 120. Step 275 caninclude receiving the test results or completion of one or more of thesteps or protocol 212 at the agent 120. Step 280 includes comparing thecompletion of steps or protocol 212 relative to the schedule of steps ortest or protocol 212 to complete according to the template 210. Step 285includes transmitting the test results or data of completion of executedsteps of the protocol 212 to the Symptom analyzer 245 or receiving thetest results or data of completion of executed steps of the protocol 212at the symptom analyzer 245.

An embodiment of the system 100 and method 200 can automatically acquireand update output of data of changes to the recommended protocol (e.g.,sequence of one or more diagnostic tests or image acquisition) 212associated with the selection of the candidate hypothesis 262.

Step 290 includes interacting or communicating between one or more ofthe agent 120, one or more the resources 105, the template 210, and thesymptom analyzer 245 to track progress of a quality of care metrics 292(See FIG. 3) directed to delivery of healthcare to the patient 115. Anembodiment of the parameters and thresholds of the quality of caremetrics 292 can be listed or stored with the disease template 210 orindependent thereof. Step 290 can be performed periodically orcontinuously through or during a portion or all of the protocolassociated with the first selection of the candidate hypothesis 262. Oneembodiment of the quality of care metrics 292 include, but are notlimited to, tracking relationship of delivery of the portion or all ofthe protocol to time to or rate of mitigation or reduction of the healthrisk to the patient, time to or rate of reduction in symptoms ofpatient, or time to rate of reduction in abnormal biometric data ofpatient, or combination thereof.

Examples of quality of care metrics directed to health risk to thepatient can be quantified by tracking or acquiring input of at least oneof the following: Acute Physiology and Chronic Health Evaluation (APACHEII) as a measure of how likely to make it out of intensive care unit;Simplified Acute Physiology (SAP) score; Glasgow Coma Score (GCS) as anassessment of consciousness; Sequential Organ Failure Assessment (SOFA)score as an assessment of person's organ function or rate of failure;Apgar Assessment of a newborn's adjustment to life; Pain perceptionprofile; visual analogue scale (VAS); quality of life metrics such asEDLQ, SF36; depression scale such as CES-D; impact of event scale (IES);or thrombosis risk assessment, or trend therein, or combination ofabove. Of course, the above list of quality of care metrics directed tohealth risk to the patient is not limiting, and other miscellaneousscores and assessments known in the medical field can be used.

For example, the system 100 can track progress of the quality of caremetric 292 via tracking time to or rate of mitigation or reduction ofhealth risk associated with or time to or rate of reduction of abnormalsymptom or biometric tracking data of the patient 115 such as chestpain, abnormal heart rate or pressure; respiratory rate or pressure;temperature; blood test parameters such as oxygen level, glucose level,iron level, white blood cell count, red blood cell count, plateletslevel, hemoglobin level, cholesterol level, lipoprotein level, troponinlevel, enzyme levels, electrolyte levels, calcium levels, BUN levels,CRP levels, homocysteine levels, etc.

For example, in response to calculating or detecting or acquiring datathat the protocol 212 of the first selection of the candidate hypothesis262 does not cause a threshold mitigation or reduction of the symptom(e.g., abnormal biometric tracking data, pain, etc.) or health risk tothe patient within a threshold time or at a threshold rate of reduction,the system 100 may re-calculate or lower the confidence 253 in the firstcandidate hypothesis 262 and respectively raise the confidence in one ormore of the remaining hypotheses 252 in the list. The remaining list ofhypotheses 252 for a symptom of chest pain can be associated with thegall bladder, or even spastic-colon (which has symptoms that can beconstrued as cardiac in nature).

Step 290 can include acquiring or receiving additional quality of caremetrics 292 at the agent 120 for communication to the output device(e.g., dashboard, workstation, kiosk, etc.) for viewing as therespective patient 115 moves through from admission to discharge fromthe institution. Examples of additional metrics 292 can include waittime for the resource 105 (e.g., wait time for admission to amedical/surgical bed, wait time between admission relative topreliminary diagnosis, etc.), and percent compliance to protocol oftemplate.

Step 295 includes comparing and reporting the tracking of quality ofcare metric 292 relative to a threshold. The metrics 292 may be reportedto departmental or institutional management or individual physicians orcaregivers for quality feedback. The decision engine 235 or otherportion of the system can compare the acquired measurement of themetrics 292 relative to a threshold, and if at least one measured metric292 falls outside the threshold range (e.g., exceeds threshold) cancause or trigger a reallocation or scheduling of resources 105. Inresponse to acquiring or measuring the at least one metric 292 fallingoutside the threshold range, the system 100 can also generate a requestfor a re-calculation or identification of hypotheses 252, or create are-calculation of confidence 253 in one candidate hypothesis 262relative to other hypotheses 252 (e.g., decreasing confidence 253 inselected candidate hypothesis 262 in proportion to increasing confidence253 in one or more other hypotheses 252). One embodiment of the decisionengine 235 or other portion of the system 100 can compare the quality ofcare metrics 292 relative to thresholds times or rates of reductiondirected to trigger or cause an alert mechanism to inform the physicianor caregivers 108 of delivery of care delivered to the patient 115 belowa threshold (e.g., time to or rate of reduction of symptom, time to orrate of reduction of health risk, etc.).

In response to updating and comparing the health risk directed to onepatient 115 in response to tracking changes in comparison to thresholdsof step 295, changes to biometric data, changes to wait times, etc.,step 298 can include changing the priority of the protocol 212,including tests or procedures or scheduling of resources 105 (e.g.,physicians, surgeons, staff, surgery or other procedural or examinationrooms, equipment such as imaging systems, etc.) relative to schedulingof resources 105 directed to other patients 115. For example, supposethe candidate hypothesis 262 was that a first patient is not cardiac.Later in the process this is proved incorrect, the patient 115 may nowbecome highly urgent for cath-lab admission for vessel opening. Inresponse to a change to the highly urgent status, the symptom analyzer245 can automatically increase value of risk associated with the patient115 to be greater than the risk value or model of all other non-urgentpatients 115, or relative to the risk value or model of non-urgentpatients waiting for surgery, and accordingly change the scheduling ofresources 105 such that that urgent patient 115 can be schedule toreceive the protocol 212 (e.g., a test or a procedure) before othernon-urgent patients 115.

The above-described steps of the method 200 can include series ofreiterations that includes re-analysis, output, selection, and executionof protocol associated with the list of candidate hypothesis correlatedto various templates 210, and yet maintain viewing and comparison to theremaining unselected candidate hypotheses and respective templates 210.Refer again to the example of the symptom of chest pain as describedabove.

The system 100 can also include one or more software receptors 300. Anembodiment of the software receptor 300 monitors data flows across aseries of patients or a patient population, and passively track/observeand pass data to the system 100 in tracking delivery of quality of care,infection management, and disease population state monitoring (i.e.looking for early indicators of potential disease outbreaks).

As the system 100 acquires data, the system 100 can detect or identifyanomalies in the acquired test results or medical condition relative tothe selection of the candidate hypothesis of the patient 115. Inresponse to detection of an anomaly or change in a biometric parameterof the patient 115, the system 100 can automatically convert or outputthe test results or medical condition associated with the anomaly into aquery to the decision engine 235. In response to the query, the decisionengine 235 can automatically parse the database of templates 210 andoutput or generate a revised list of hypotheses 252.

The system 100 can further output an alert in response to detection oracquiring data indicative of a contra-indicator (e.g., actions that mayincrease health risk to patient) via the symptom analyzer 245 such thatthe physician can be alerted to errors of interpretation, null ofselection of candidate hypothesis, and potential alternate candidatehypotheses. Thereby, a technical effect of the system 100 can includethe ability to continually aid the physician with medical knowledgeapplied uniquely to the situation or medical condition of the patient athand. The system 100 and method 200 can also enhance delivery ofhealthcare to patients 115 convolved with multi-disease states. Themedical condition of patients (e.g., older patients or chronically illpatients) can go unstable, or new failure mode can develop.

The template 210 can be modified to accommodate the interaction withvarious bodies of knowledge, including data of experiences in similarcases, or data of cases with some equivalence may be shared. The system100 may output diagnostic protocols 212 that are significantly differentor enhanced relative to different stages of disease states of thepatient. The system 100 can also acquire or receive clinical bestpractices and add to the protocol of various template 210 s asappropriate. In this fashion, the integration of new knowledge with theclinical practitioner can occur on an “as-needed” basis.

The following is a description of management of quality of delivery ofhealthcare to a patient at a long-term care facility via the systemdescribed above. The system 100 can acquire the protocol 212 of a planof a quality of care metrics 292 to address needs and risks for eachpatient, and arrange protocol 212 of the plan of the quality of caremetrics 292 in a template 210 associated with various conditions fordelivery of healthcare at the long-term care facility. At a long-termcare facility, the protocol 212 for the delivery of healthcare mayinvolve lesser need or no need for diagnostic tests or procedures.

The agent 120 can receive data representative of the quality of caremetric 292 and relay to the software receptor 300. The software receptor300 can forward the data to the EMR 202 according to Institutionalpolicy. The system 100 can acquire or receive quality of care metrics292 to combine with other data (e.g., historical data of an EMR 202,current data acquired at the software receptor 300, and thresholdcriteria of quality of care metrics 292) so as to calculate or outputthe general real-time values or measure of quality of care metrics 292delivered to the particular patient 115 relative to the threshold (e.g.,to trigger an alarm).

For example, in a case of a comatose medical condition, the plan of careprotocol 212 as stored in a template 210 may include the quality of caremetric 292 that the patient 115 be turned at a threshold time interval.If the agent 120 associated with the patient 115 acquires or measuresthe quality of care metric 292 (e.g., time data via clock) that detectsthat no movement of the patient 115 has occurred beyond threshold timeinterval, the agent 120 can cause communication of a signal to triggeran alarm at the output device 150. The system 100 can also outputchanges in alarm conditions associated with changes in acquiredthresholds in quality of care metrics 292 described above. The system100 can also track changes in quality of care metrics 292 for output inreports to benefit providers (long term care insurance), legalguardians, or family members. The subject matter described hereinprovides a process to enhance performance of long term careorganizations, and may help with accreditation and comparison of carefacilities.

FIG. 4 illustrates an embodiment of a dashboard 400 illustrative to theoutput from the system 100. The dashboard 400 includes an illustrationof the patient identifier 402, the list of hypotheses 252, the selectionof the candidate hypothesis 262, the list of protocol or instructionassociated with each hypotheses 252, the confidence 253 in eachhypotheses, and the one or more quality of care metrics 292 tracked bythe system 100. The quality of care metrics 292 may be directed to allpatients 115 or individually to each patient 115.

A technical effect of the above-described system 100 and method 200includes enhancement of management of quality of delivery of healthcarein a workflow in general real-time. The system 100 and method 200 cangenerally acquire the flow of information or acquired data from thevarious components of the system 100 or resources 105 and combine orarrange in a manner to aid the physician in decision-making and director steer the diagnostic investigation of the patient 115. Conformance toaccepted methods and protocols 212 can aid timely execution, andpotentially minimize mistakes or misses through continuity of decisionmaking with respect a specific patient.

Another technical of the system 100 and method 200 is to provide a meansto monitor quality of care delivered to the patient 115 in generalreal-time, a means to automatically incorporate patient telemetry intocare delivery, a means to monitor trends in quality of care delivery,and a means to enhance compliance with changes in care delivery. Anothertechnical effect of the system 100 and method 200 includes reducinginformation overload to Caregivers by providing high value knowledge atthe point of care in general real-time.

Although the systems 100 and methods 200 are described with respect tospecific healthcare environment, systems 100 and methods 200 can beextended to any nature or type of workflow. Other examples includediagnostic equipment that supports multiple test types reconfigures selfto support high priority customer need. Alternatively, a departmentschedule can have one operational profile one day or even one hour tosuit a demand, and be reprogrammed with another operational schedule tosuit a different demand in time. The system 100 and method 200 are alsooperable to create a schedule that accommodates combination orpermutations of conditions. Thereby, the system 100 and method 200afford flexibility and control of a workflow relative to those managedas only a linear function.

Although the subject matter is described herein with reference tomedical diagnostic or cardiac treatment applications, it should be notedthat the subject matter is not limited to this or any particularapplication or environment or environment (e.g., industrial, commercial,etc.).

This written description uses examples to disclose the subject matter,including the best mode, and also to enable one skilled in the art tomake and use the invention. The patentable scope of the subject matteris defined by the following claims, and may include other examples thatoccur to those skilled in the art. Such other examples are intended tobe within the scope of the claims if they have structural elements thatdo not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal languages of the claims.

The invention claimed is:
 1. A method of managing a quality of deliveryof healthcare to a patient, the method comprising: parsing, using aprocessor, a medical record for a patient, to identify at least onesymptom data to compare to at least one keyword in each of a pluralityof templates, the at least one keyword associated with a medicalcondition and a protocol to diagnose or treat the medical condition,each protocol comprising a plurality of tasks to be executed to completethe protocol according to a schedule associated with the protocol;outputting, using the processor, a) a plurality of candidate hypothesiseach associated with a different templates and b) a confidence levelassociated with each candidate hypothesis; automatically outputting,using the processor, the protocol associated with a selected candidatehypothesis, the outputting to provide a representation of the protocolvia an output device; tracking completion of a portion of the protocolassociated with the selected candidate hypotheses to deliver healthcareto the patient, wherein tracking completion of the portion of theprotocol includes tracking completion of tasks executed according to theschedule associated with the protocol; tracking a change in a quality ofcare metric directed to the patient with completion of the portion theprotocol, the quality of care metric including at least one of a) a timeto rate of reduction in a health risk to the patient and b) a time to orrate of reduction in symptom or abnormal biometric data of the patient;outputting an alert using the processor in response to the quality ofcare metric exceeding a threshold; and decreasing confidence in theselected candidate hypothesis and increasing confidence in one or moreof the other plurality of candidate hypotheses triggered by acquiringthe at least one quality of care metric exceeding the threshold.
 2. Themethod of claim 1, further comprising: outputting via the output devicean illustration of the at least one quality of care metric relative tothe threshold and the completion of the portion of the protocol.
 3. Themethod of claim 1, further comprising: increasing a priority of thepatient relative to other patients in the schedule of resources if theat least one quality of care metric that exceeds the threshold such thatthe system schedules the patient to receive use of the resources beforethe other patients.
 4. The method of claim 1, further comprising:generating a request for a re-calculation of a list of candidatehypotheses triggered by acquiring the at least one quality of caremetric exceeding the threshold.
 5. The method of claim 1, wherein thehealth risk to the patient includes at least one of mortality risk;acute physiology and chronic health evaluation (APACHE II); simplifiedacute physiology (SAP) score; Glasgow coma score (GCS); sequential organfailure assessment (SOFA) score; Apgar assessment; pain perceptionprofile; visual analogue scale (VAS); quality of life metrics;depression scale; impact of event scale (IES); and thrombosis riskassessment.
 6. The method of claim 1, wherein symptom or biometric dataof the patient includes one or more of the following: a chest pain, anabnormal heart rate or pressure; a respiratory rate or pressure; atemperature; and a blood test parameters such as oxygen level, glucoselevel, iron level, white blood cell count, red blood cell count,platelet level, hemoglobin level, cholesterol level, lipoprotein level,troponin level, enzyme level, electrolyte level, calcium level, BUNlevel, CRP level, and homocysteine level.
 7. A system to manage deliveryof healthcare to a patient, the system comprising: a controller with amemory in communication with a processor, the memory including programinstructions for execution by the processor to: parse a medical recordfor a patient, to identify at least one symptom data to compare to atleast one keyword in each of a plurality of templates, the at least onekeyword associated with a medical condition and a protocol to diagnoseor treat the medical condition, each protocol comprising a plurality oftasks to be executed to complete the protocol according to a scheduleassociated with the protocol; output a) a plurality of candidatehypothesis each associated with a different templates and b) aconfidence level associated with each candidate hypothesis;automatically output the protocol associated with a selected candidatehypothesis, the outputting to provide a representation of the protocolvia an output device; track completion of a portion of the protocolassociated with the selected candidate hypotheses to deliver healthcareto the patient, wherein tracking completion of the portion of theprotocol includes tracking completion of tasks executed according to theschedule associated with the protocol; track a change in a quality ofcare metric directed to the patient with completion of the portion theprotocol, the quality of care metric including at least one of a) a timeto rate of reduction in a health risk to the patient and b) a time to orrate of reduction in symptom or abnormal biometric data of the patient;output an alert in response to the quality of care metric exceeding athreshold; and decrease confidence in the selected candidate hypothesisand increasing confidence in one or more of the other plurality ofcandidate hypotheses triggered by acquiring the at least one quality ofcare metric exceeding the threshold.
 8. The system of claim 7, thecontroller further operable to: decrease confidence in the selectedcandidate hypothesis and increasing confidence in one or more of theother plurality of candidate hypotheses triggered by acquiring the atleast one quality of care metric exceeding the threshold.
 9. The systemof claim 7, the controller further operable to: output to an outputdevice an illustration of the at least one quality of care metricrelative to the threshold and the completion of the portion of theprotocol.
 10. The system of claim 7, the controller further operable to:increase a priority of the patient relative to other patients in theschedule of resources if the at least one quality of care metric thatexceeds the threshold such that the system schedules the patient toreceive use of the resources before the other patients.
 11. The systemof claim 7, the controller further operable to: generate a request for are-calculation of a list of candidate hypotheses triggered by acquiringthe at least one quality of care metric exceeding the threshold.
 12. Thesystem of claim 7, wherein the health risk to the patient includes atleast one of mortality risk; acute physiology and chronic healthevaluation (APACHE II); simplified acute physiology (SAP) score; Glasgowcoma score (GCS); sequential organ failure assessment (SOFA) score;Apgar assessment; pain perception profile; visual analogue scale (VAS);quality of life metrics; depression scale; impact of event scale (IES);and thrombosis risk assessment.
 13. The system of claim 7, furthercomprising an agent to acquire the symptom or biometric data forcommunication to the controller, the symptom or biometric data of thepatient comprising at least one of the following: a chest pain; anabnormal heart rate or pressure; a respiratory rate or pressure; atemperature; and a blood test parameters such as oxygen level, glucoselevel, iron level, white blood cell count, red blood cell count,platelet level, hemoglobin level, cholesterol level, lipoprotein level,troponin level, enzyme level, electrolyte level, calcium level, BUNlevel, CRP level, and homocysteine level.
 14. The system of claim 7,wherein the quality of care metric includes a time since last turnoverof the patient relative to a threshold.
 15. The system of claim 8,wherein the confidence includes a percentage of terms in the medicalrecord that match the keyword in each of the plurality of templates. 16.A non-transitory computer-readable storage medium including a set ofinstructions to be executed by a processor, the set of instructions,when executed, to implement a method of managing a quality of deliveryof healthcare to a patient, the method comprising: parsing a medicalrecord for a patient, to identify at least one symptom data to compareto at least one keyword in each of a plurality of templates, the atleast one keyword associated with a medical condition and a protocol todiagnose or treat the medical condition, each protocol comprising aplurality of tasks to be executed to complete the protocol according toa schedule associated with the protocol; outputting a) a plurality ofcandidate hypothesis each associated with a different templates and b) aconfidence level associated with each candidate hypothesis;automatically outputting the protocol associated with a selectedcandidate hypothesis, the outputting to provide a representation of theprotocol via an output device; tracking completion of a portion of theprotocol associated with the selected candidate hypotheses to deliverhealthcare to the patient, wherein tracking completion of the portion ofthe protocol includes tracking completion of tasks executed according tothe schedule associated with the protocol; tracking a change in aquality of care metric directed to the patient with completion of theportion the protocol, the quality of care metric including at least oneof a) a time to rate of reduction in a health risk to the patient and b)a time to or rate of reduction in symptom or abnormal biometric data ofthe patient; outputting an alert in response to the quality of caremetric exceeding a threshold; and decreasing confidence in the selectedcandidate hypothesis and increasing confidence in one or more of theother plurality of candidate hypotheses triggered by acquiring the atleast one quality of care metric exceeding the threshold.
 17. Thecomputer-readable storage medium of claim 16, wherein the method furthercomprises: outputting via the output device an illustration of the atleast one quality of care metric relative to the threshold and thecompletion of the portion of the protocol.
 18. The computer-readablestorage medium of claim 16, wherein the method further comprises:increasing a priority of the patient relative to other patients in theschedule of resources if the at least one quality of care metric thatexceeds the threshold such that the system schedules the patient toreceive use of the resources before the other patients.
 19. Thecomputer-readable storage medium of claim 16, wherein the method furthercomprises: generating a request for a re-calculation of a list ofcandidate hypotheses triggered by acquiring the at least one quality ofcare metric exceeding the threshold.
 20. The computer-readable storagemedium of claim 16, wherein symptom or biometric data of the patientincludes one or more of the following: a chest pain, an abnormal heartrate or pressure; a respiratory rate or pressure; a temperature; and ablood test parameters such as oxygen level, glucose level, iron level,white blood cell count, red blood cell count, platelet level, hemoglobinlevel, cholesterol level, lipoprotein level, troponin level, enzymelevel, electrolyte level, calcium level, BUN level, CRP level, andhomocysteine level.